Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinea...
Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies
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Publisher
England: BioMed Central Ltd
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Language
English
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Publisher
England: BioMed Central Ltd
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Contents
Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied...
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Full title
Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies
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TN_cdi_doaj_primary_oai_doaj_org_article_6f2d4989c80b4894bd158399f4565d52
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6f2d4989c80b4894bd158399f4565d52
Other Identifiers
ISSN
1471-2288
E-ISSN
1471-2288
DOI
10.1186/s12874-022-01542-8
